Courses

This course provides a rigorous review of basic linear regression and techniques both for cross-sectional and panel applications. The course then covers further topics which are important in applied econometric analysis based on individual level data and longitudinal data. These topics include a discussion of the asymptotic theory for nonlinear estimation techniques (MLE, Nonlinear Least Squares), discrete choice models, limited dependent variables models, and linear quantile regressions. The course provides an up-to-date treat¬ment at the level of Wooldridge's textbook on “Econometric Analysis of Cross Section and Panel Data”. The course will regularly discuss the causal interpretation of econometric estimates. The focus of the course is both on understanding the methodological concepts and on how to apply them. Students will learn to implement the estimation methods using the econometric package Stata.

Lectures by A. Kriwoluzky:
This class covers the essentials to estimate DSGE models with Bayesian methods. We start by deriving the state-space form of a DSGE model. In a next step, we introduce the Kalman Filter, a very useful tool to extract unobserved components from time series or to evaluate the likelihood of a DSGE model. The exercise classes will apply the simple New Keynesian model to extract monetary policy shocks.
Equipped with the basics, we start exploring the Bayesian way to estimate models. More precisely, we will introduce the Prior and the Posterior distribution of parameters. Students will learn how to evaluate the Posterior distribution numerically using different sampling algorithms. In the exercise class, we discuss how a Bayesian model can be employed to forecast economic variables.
The final part will see the introduction of the Dynare software package that is usually used to solve and estimate DSGE models. After the introduction of the basic setup of a Dynare file, we will put Dynare to work. Finally, we aim to consider complex models such as the Smets and Wouters model (2007, AER).

Lectures by F. Heinemann:
This part of the course covers topics such as determinacy of the price level, bubbles, equilibrium multiplicity, strategic uncertainty, and current limits of DSGE models. More information will be provided here.

Literature:
Will be announced during the lectures.

Time frame (date of first and last class):
- Lectures by A. Kriwoluzky: April 12 till May 15 on the following days: April 12, 17, 24 & May 10, 15
- Lectures by F. Heinemann: every Wednesday from May 22 to July 10 (except July 3)

The first part of the course studies monetary theory: how future expected money supply affects the current price level, why money can be written in the utility function and what is required to determine a unique equilibrium with rational expectations. Turning to the foundations of New Keynesian Macroeconomics, we analyze why monopolistic competition leads to an active role for monetary policy, derive the forward looking Phillips curve and study optimal monetary policy.
The second part of the course is dedicated to the solution of DSGE models in general and in particular models in which labor market frictions play a prominent role. It is designed to develop and sharpen students’ prior knowledge of dynamic macroeconomics and econometrics with a mixture of lectures on state-of-the-art solution and estimation techniques for macroeconomic models and application of the techniques with standard software packages and models from the literature. Students are required at a minimum to have successfully completed the AMA I course and possess a basic understanding of time-series and linear-model econometrics.

Methods of modern macroeconomics for researchers in the field: Stationary Markov environments, state-space methods, stochastic difference equations, dynamic programming and Lagrangian methods, complete markets, dynamic stochastic general equilibrium models, solution techniques, empirical consequences of macroeconomic shocks; structural estimation, the Ramsey problem, dynamic stochastic general equilibrium (DSGE) models. To this end a number of theoretical and empirical concepts are presented. Examples include the computation of impulse response functions, structural vector autoregressions, as well as an introduction to structural estimation. On the normative side the concept of Ramsey optimal policy is presented.

The intention of the course is to familiarize students with the standard tool of modern economic theory and to train them in applying these tools to actual economic problems. It is particularly devoted to market failures and welfare economics. The first part (Part III in MWG) outlines properties of competitive markets and welfare analysis in a partial equilibrium context. It then focuses on the three classical conditions under which market outcomes lead to an inefficient allocation of resources: externalities, imperfect competition and asymmetric information. The second part (Part V in MWG) addresses fundamental issues of welfare economics from the perspective of a policy maker who designs and implements collective decisions. It focuses in particular on social choice theory, the foundations of bargaining and welfare economics, and mechanism design. The course addresses these issues both from a positive and normative perspective.

The intention of the course is to familiarize students with the standard tool of modern economic theory and to train them in applying these tools to actual economic problems. It is particularly devoted to market failures and welfare economics. The first part (Part III in MWG) outlines properties of competetive markets and welfare analysis in a partial equilibrium context. It then focuses on the three classical contidions under which market outcomes lead to an inefficient allocation of resources: externalities, imperfect competition and asymmetric information. The second part (Part V in MWG) addresses fundamental issues of welfare economics from the perspective of a policy maker who desingns and implements collective decisions. It focuses in particular on social choice theory, the foundations of bargaining and welfare economics, and mechanism design. The course addresses these issue both from a positive and normative perspective.
Literature:
Mas-Colell, Whinston, and Green (1995), Microeconomic Theory (MWG), Part III and Part V
Times and Venues:
April 16 - May 7 at ESMT Berlin, Schlossplatz 1, in the corresponding rooms:
April 16, 30 and May 7: Bookshop
April 23: Seminar room 00.17
May 14 - July 11 at FU Berlin, Garystrasse 21, room 108a
June 18 - July 9 at HUB, Room 22, Spandauer Strasse 1

This course is devoted to the core elements of microeconomics. We study both the economics of households and the economics of firms and introduce general equilibrium with particular attention to the two welfare theorems. We also examine decisions under uncertainty, introducing expected and non-expected utility theories. The analysis of choice under uncertainty leads to the examination of financial markets and to strategic interaction problems, which we introduce through the key notions in noncooperative game theory, in particular Nash equilibrium and its most important refinements. Also matching problems will be discussed.

The course deals with advanced estimation techniques in modern econometrics and standard single equation and systems of equations models and also covers time series analysis including multiple time series analysis.

Since this course aims primarily at Masters Students, only BDPEMS students with no basic knowledge in econometrics may be admitted for this course conditional on a personal authorization by Prof. Nikolaus Hautsch, following the Beginners' Track in Econometrics. All other students have to attend Econometrics I (Time Series Analysis).

The course is split in two parts. The first part will be taught by Anton Velinov and Niels Aka from the DIW Berlin and the exam is going to take place in December. The grading of the first part is based on the assignments (20%) and an exam (80%) at the end of the term. Each part of the course is given a 50% weight of the total grade.

The second part will be taught by Lars Winkelmann from the Free University Berlin and Annika Schnücker from the DIW Berlin. More information on that is to come.

The course aims at providing the basic concepts and methods for analysing time series data. The focus is on univariate modelling tools. The lecture begins with classical components models. Then we cover different types of stochastic processes like ARIMA and GARCH models, deal with the unit root methodology and procedures for forecasting as well as for the specification, estimation and validation of models. Multivariate extensions are demonstrated, with emphasis on vector autoregressive (VAR) processes and its application in causality and impulse response analyses. Nonstationary systems with integrated and cointegrated variables will also be treated.

In the tutorials the time series methods are applied to empirical data. We will intensively make use of econometric software packages. A deeper insight into advanced methods and additional topics is offered by means of assignments, empirical studies and/or literature reviews.

The course aims at providing the basic concepts and methods for analysing time series data. The focus is on univariate modelling tools. The lecture begins with classical components models. Then we cover different types of stochastic processes like ARIMA and GARCH models, deal with the unit root methodology and procedures for forecasting as well as for the specification, estimation and validation of models. Multivariate extensions are demonstrated, with emphasis on vector autoregressive (VAR) processes and its application in causality and impulse response analyses. Nonstationary systems with integrated and cointegrated variables will also be treated.

In the tutorials (which take place at room 025) the time series methods are applied to empirical data. We will intensively make use of econometric software packages. A deeper insight into advanced methods and additional topics is offered by means of assignments, empirical studies and/or literature reviews.

The course aims at providing the basic concepts and methods for analysing time series data. The focus is on univariate modelling tools. The lecture begins with classical components models. Then we cover different types of stochastic processes like ARIMA and GARCH models, deal with the unit root methodology and procedures for forecasting as well as for the specification, estimation and validation of models. Multivariate extensions are demonstrated, with emphasis on vector autoregressive (VAR) processes and its application in causality and impulse response analyses. Nonstationary systems with integrated and cointegrated variables will also be treated.
In the tutorials the time series methods are applied to empirical data. We will intensively make use of econometric software packages. A deeper insight into advanced methods and additional topics is offered by means of assignments, empirical studies and/or literature reviews.

This course provides a rigorous review of basic linear regression and techniques both for cross-sectional and panel applications. The course then covers further topics which are important in applied econometric analysis based on individual level data and longitudinal data. These topics includes a discussion of the asymptotic theory for nonlinear estimation techniques (MLE, Nonlinear Least Squares), discrete choice models, limited dependent variables models, and linear quantile regressions. The course provides an up-to-date treat-ment at the level of Wooldridge's textbook on “Econometric Analysis of Cross Section and Panel Data”. The course will regularly discuss the causal interpretation of econometric estimates. The focus of the course is both on understanding the methodological concepts and on how to apply them. Students will learn to implement the estimation methods using the econometric package Stata.

Prerequisites
Knowledge of econometrics at the level of the courses “Econometric Methods 1” (First Master course) or “Econometrics I” (BDPEMS).

Grade
The grade will be based on a written final exam (90 minutes, two dates).

Further Information

There will be problem sets with theoretical and empirical exercises which will be assigned as voluntary homeworks for Master students and as mandatory homeworks for PhD students. Homeworks are to be submitted by groups of 2-4 students. The homeworks will be corrected for all students and the same number of credits will be given for all group members. However, the homeworks do not count as part of the final grade for master students. PhD students must obtain at least 50% of all possible credits for the graded homeworks in order to be able to write the final exam but the final grade for the PhD students will only be based on the final exam.

Further references, particularly regarding the method of Quantile Regression and the application of the methods, will be given in the course. The basic estimation techniques will be implemented in the PC Pool using the econo¬metric package Stata.

This course deals with advanced estimation techniques in modern econometrics. In the first part we study generalized methods of moments (GMM) estimation as well as pseudo-maximum likelihood techniques and their applications to different types of single-equation models and multiple-equation systems. If time, a brief introduction to Bayesian econometric methods will be given. The second part covers non- and semiparametric methods in econometrics. We will study basic Kernel density estimation, nonparametric regression techniques and estimation of partially linear and additive models. A deep knowledge of the techniques conveyed in this course is extremely useful since they are applied in various areas in modern econometrics, including time series econometrics, microeconometrics, panel econometrics as well as financial econometrics.

This course deals with advanced estimation techniques in modern econometrics. In the first part we study generalized methods of moments (GMM) estimation as well as pseudo-maximum likelihood techniques and their applications to different types of single-equation models and multiple-equation systems. If time, a brief introduction to Bayesian econometric methods will be given. The second part covers non- and semiparametric methods in econometrics. We will study basic Kernel density estimation, nonparametric regression techniques and estimation of partially linear and additive models. A deep knowledge of the techniques conveyed in this course is extremely useful since they are applied in various areas in modern econometrics, including time series econometrics, microeconometrics, panel econometrics as well as financial econometrics.

This course deals with advanced estimation techniques in modern econometrics.
Main topics include generalized methods of moments (GMM) estimation for single-equation models and multiple-equation models, information theoretic approaches as well as pseudo-maximum likelihood techniques. Furthermore, an introduction to Bayesian econometric methods will be given. Here the focus is on fundamental principles of Bayesian inference, Markov chain Monte-Carlo (MCMC) methods as well as different applications of Bayesian inference. The third and forth part covers non- and semiparametric methods in econometrics. We will study basic Kernel density estimation, nonparametric regression techniques and estimation of partially linear and additive models. A deep knowledge of the techniques conveyed in this course is extremely useful since they are applied in various areas in modern econometrics, including time series econometrics, micro econometrics, panel econometrics as well as financial econometrics.

Covers positive accounting theory and capital market-based accounting research. Topics in the area of positive accounting research cover issues like accounting choice, disclosure quality, earnings management as well as governance-related accounting questions. Capital market-based accounting research focues on topics like the pricing impact of financial accounting disclosure on capital markets, the connection between accounting and the cost of capital or the interplay of financial accounting and corporatefinance decisions. Literature: None. For a reading list of current papers, refer to the full syllabus.

Methods of modern macroeconomics for researchers in the field: Stationary Markov environments, state-space methods, stochastic difference equations, dynamic programming and Lagrangian methods, complete markets, dynamic stochastic general equilibrium models, solution techniques, empirical consequences of macroeconomic shocks; structural estimation, the Ramsey problem, dynamic stochastic general equilibrium (DSGE) models. To this end a number of theoretical and empirical concepts are presented. Examples include the computation of impulse response functions, structural vector autoregressions, as well as an introduction to structural estimation. On the normative side the concept of Ramsey optimal policy is presented.

The following topics will be taught: Asset pricing; advanced preference theory such as Epstein-Zin; dynamic contracts and applications; growth models, OLG models; Money and models of price and wage rigidities; economic policy and time consistency, applied VAR analysis.This will be complemented by deepening the knowledge regarding mathematical and econometric tools, such as MATLAB and/or EViews.

Organisation:The first part of the course, i.e. from April 11 to May 23, 2012 will be taught by Frank Heinemann at the TU Berlin. Monique Ebell will hold the second part, i.e. from May 30 to July 11, 2012 at HU Berlin.

The objective of this course is to enable M.A. and Ph.D. students to use macroeconomic concepts and techniques for their own research. This leads to a higher level of formalization in this lecture than in the introductory lecture (IAMA).

Contents (Prof. Weinke): This course develops dynamic stochastic general equilibrium (DSGE) models and uses them for positive and normative macroeconomic analysis. To this end a number of theoretical and empirical concepts are presented. Examples include the computation of impulse response functions, structural vector autoregressions, as well as an introduction to structural estimation. On the normative side the concept of Ramsey optimal policy is presented.
Literatur

The objective of this course is to teach M.A. and Ph.D. students to use macroeconomic concepts and techniques for their own research and incorporates a higher degree of formal analysis than in the introductory master’s lecture (IAMA).

Part II (Prof. Weinke): Dynamic stochastic general equilibrium (DSGE) models for positive and normative macroeconomic analysis. To this end a number of theoretical and empirical concepts are presented: The computation of impulse response functions, structural vector autoregressions, as well as an introduction to structural estimation. On the normative side the concept of Ramsey optimal policy is presented.

The objective of this lecture is to enable M.A. and Ph.D. students to
use macroeconomic concepts for their own research. This leads to a higher
level of formalization in this lecture than in the introductory lecture
(IAMA).

Contents (Prof. Weinke): This course develops dynamic stochastic general
equilibrium (DSGE) models and uses them for positive and normative
macroeconomic analysis. To this end a number of theoretical and empirical
concepts are presented. Examples include the computation of impulse
response functions, structural vector autoregressions, as well as an
introduction to structural estimation. On the normative side the concept
of Ramsey optimal policy is presented.

Contents Prof. Weinke: This course develops dynamic stochastic general equilibrium (DSGE) models and uses them for positive and normative macroeconomic analysis. To this end a number of theoretical and empirical concepts are presented. Examples include the computation of impulse response functions, structural vector autoregressions, as well as an introduction to structural estimation. On the normative side the concept of Ramsey optimal policy is presented.

Contents Prof. Weinke: This course develops dynamic stochastic general equilibrium (DSGE) models and uses them for positive and normative macroeconomic analysis. To this end a number of theoretical and empirical concepts are presented. Examples include the computation of impulse response functions, structural vector autoregressions, as well as an introduction to structural estimation. On the normative side the concept of Ramsey optimal policy is presented.

The objective of this course is to teach M.A. and Ph.D. students to use macroeconomic concepts and techniques for their own research and incorporates a higher degree of formal analysis than in the introductory master’s lecture (IAMA).

Part II (Prof. Weinke): Dynamic stochastic general equilibrium (DSGE) models for positive and normative macroeconomic analysis. To this end a number of theoretical and empirical concepts are presented: The computation of impulse response functions, structural vector autoregressions, as well as an introduction to structural estimation. On the normative side the concept of Ramsey optimal policy is presented.

The first part by Frank Heinemann analyzes how future expected money supply affects the current price level, why money can be written in the utility function and what is required to determine a unique equilibrium with rational expectations. Turning to the foundations of New Keynesian Macroeconomics, we analyze why monopolistic competition leads to an active role for monetary policy, derive the forward looking Phillips curve and study optimal monetary policy.

The second part (starting June 15) of this course deals with search and matching and is taught by Mathias Trabandt from Free University. The syllabus and organizational details about the second part of the course will be published in due course at www.wiwiss.fu-berlin.de/trabandt.

The first part (Heinemann) analyzes how future expected money supply affects the current price level, why money can be written in the utility function and what is required to determine a unique equilibrium with rational expectations. Turning to the foundations of New Keynesian Macroeconomics, we analyze why monopolistic competition leads to an active role for monetary policy, derive the forward looking Phillips curve and study optimal monetary policy.

This course is concerned with situations in which decisions are made sequentially. The fundamental tradeoff at stake consists in balancing immediate reward with unpredictable future rewards. These situations can be found in a wide variety of areas ranging from marketing (e.g. dynamic pricing) to the environment (e.g. water management). In this course, we will primarily focus on applications in the field of management science.
The approach is based on Markov decision processes and more generally (stochastic) Dynamic Programming, which provides a set of general methods for making sequential decisions under uncertainty.

The theories and methods of social network analysis have increasingly been harnessed to better understand a diverse array of topics, such as the spread of obesity, the diffusion of innovations, mobility and risk-taking behavior in tournaments, and brokerage and status positions in markets. This course offers an introduction to the theoretical perspectives and quantitative methods of the network-analytic tradition. A number of key concepts will be introduced, together with opportunities to apply corresponding methods and approaches to measurement using data made available in class. The literature on networks is approached with two goals in mind: (1) to understand the foundations of social network theory and (2) to apply methods.

The theories and methods of social network analysis have increasingly been harnessed to better understand a diverse array of topics, such as the spread of obesity, the diffusion of innovations, mobility in labor markets, risk-taking behavior in tournaments, and affiliation-based market signaling. This course offers an introduction to the theoretical perspectives and quantitative methods of the network-analytic tradition. A number of key concepts will be introduced, together with opportunities to apply corresponding methods and approaches to measurement using data made available in class. The literature on networks is approached with two goals in mind: (1) understanding the foundations of social network theory and (2) applying methods.

Exam: Project work and presentations.

Please note that this class starts at 9am s.t..

The first session (18.10.12) is taking place in the ESMT Admin Building, room 0.35 on the ground floor. Please use the entrance on Breite Str. 1. All further sessions are taking place in the ESMT Learning Center. Please use the entrance Schlossplatz 1 and refer to the info screen for room numbers.

The theories and methods of social network analysis have increasingly been harnessed to better understand a diverse array of topics, such as the spread of obesity, the diffusion of innovations, mobility in labor markets, risk-taking behavior in tournaments, and affiliation-based market signaling. This course offers an introduction to the theoretical perspectives and quantitative methods of the network-analytic tradition. A number of key concepts will be introduced, together with opportunities to apply corresponding methods and approaches to measurement using data made available in class. The literature on networks is approached with two goals in mind: (1) understanding the foundations of social network theory and (2) applying methods.

The course is designed to impart profound understanding of the economic principles and managerial practices on a range of topics pertaining to the protection of intellectual property in the realm of technical inventions. It will include an economic analysis of the incentives created for firms to engage in costly and risky R&D endeavors that (i) result from the design of the underlying IP regime itself as well as from (ii) strategic interaction of firms within this system. Moreover, we will scrutinize how firms can use intellectual property rights to appropriate the value created from their innovative activities by either exploiting them themselves or by using it for contracting with other firms in the market for technology.

Management Science II - Part 2: Industrial Organization

Instructor: Özlem Bedre-Defolie

This course familiarizes students with classical statistical methods of management research and theoretical models in industrial organization and strategic management. The second part of the course analyzes in depth competitive strategies of vertical relations and control (B to B contracting), vertical foreclosure, entry deterrence, horizontal foreclosure (tying and bundling strategies), and economics of platforms.

Evaluation:
Grading is based on one individual assignment for which each student is expected to write one referee report on a recent research paper. The instructors will provide a list of research papers on the topics of each part of the course from which students could choose one paper to prepare a referee report. The list of research papers will be provided during the course.

The course will take place in room 00.21 or 00.17, Schlossplatz 1. The session on May 8 will take place in room 'Bookshop'. The sessions on May 15 and July 17 will take place in room 0.35 Admin Building - please use entrance Breite Str. 1.

The course Management Science II is divided into two consecutive modules: The first module encompasses intellectual property rights and the market for technology while the second module covers marketing models. Time I and Venue I above refer to the first module, Time II and Venue II to the second module.

Please refer to the downloads below for details (course outline and format, reading list, etc.) about the two modules.

The course Management Science II is divided into two consecutive modules: the first module encompasses marketing models while the second module covers intellectual property rights and the market for technology. Time I and Venue I above refer to the first module, Time II and Venue II to the second module.

Please refer to the dowloads below for details (course outline and format, reading list, etc.) about the two modules.

The course Management Science II is divided into two consecutive modules: The first module encompasses intellectual property rights and the market for technology while the second module covers marketing models. Time I and Venue I above refer to the first module, Time II and Venue II to the second module.

The aim of microeconometrics is to analyze individual behavior on the basis of micro data (crosssection and panel data) of individuals, households, and firms. The standard linear regression model is generally not applicable to micro data due to the non-metric measurement and censoring of dependent variables at the individual level, selectivity and incomplete observability of endogenous variables, and the dependence of individual observations over time. The empirical methods most frequently applied in empirical microeconomics are surveyed and several applications in empirical microeconomics are presented. Students learn how to apply these methods using real-world microdata and the software package STATA.

This course is devoted to the economic theory of preferences and choice, consumer choice, demand, production, market equilibrium, decision making under uncertainty, and game theory. The intention of the course is to familiarize students with the advanced tools of modern microeconomic theory.

This course is devoted to decision making under uncertainty and the economics of asymmetric information. The first topic introduces the Von-Neumann-Morgenstern decision model which is used in many areas of modern economics where risk plays a role (macroeconomics, finance, etc.). The course studies the foundations of this model and alternative approaches. The second part focuses on economic settings with asymmetric information. With the help of game theoretic tools, we study the working of markets with asymmetric information, bilateral trading problems with moral hazard and adverse selection, and the theory of mechanism design. The intention of the course is to familiarize students with the standard tools of modern economic theory and to train them in applying these tools to actual economic problems.

This course is devoted to market failures and welfare economics. The first part focuses on the three classical conditions under which market outcomes lead to an inefficient allocation of resources: externalities, imperfect competition and asymmetric information. It addresses these questions both from a positive and normative perspective. The second part addresses fundamental issues of welfare economics from the perspective of a policy maker who designs and implements collective decisions. It focuses in particular on social choice theory, the foundations of bargaining and welfare economics, and mechanism design. The intention of the course is to familiarize students with the standard tools of modern economic theory and to train them in applying these tools to actual economic problems.

Literature:
Mas-Colell, Whinston, and Green (1995), Microeconomic Theory, Part III and Part V

The course provides a rigorous and systematic introduction into the theory of markets and organizations at a level geared to Ph.D. students. It covers all areas of microeconomics on an advanced level. Particular emphasize is given to the theory of asymmetric information and incentives.

Note: The first part (April 16 to May 21, 2012) takes place at the ESMT, the second part (May 28 to July 9, 2012) takes place at Spandauer Str. 1.

This course is devoted to market failures and welfare economics. The first part focuses on the three classical conditions under which market outcomes lead to an inefficient allocation of resources: externalities, imperfect competition and asymmetric information. It addresses these questions both from a positive and normative perspective. The second part addresses fundamental issues of welfare economics from the perspective of a policy maker who designs and implements collective decisions. It focuses in particular on social choice theory, the foundations of bargaining and welfare economics, and mechanism design. The intention of the course is to familiarize students with the standard tools of modern economic theory and to train them in applying these tools to actual economic problems.

Literature:
Mas-Colell, Whinston, and Green (1995), Microeconomic Theory, Part III and Part V

This course is devoted to the core elements of microeconomics. We study both the economics of households and the economics of firms and introduce general equilibrium with particular attention to the two welfare theorems. We also examine decisions under uncertainty, introducing expected and non-expected utility theories. The analysis of choice under uncertainty leads to the examination of financial markets and to strategic interaction problems, which we introduce through the key notions in noncooperative game theory, in particular Nash equilibrium and its most important refinements.

Literature: Mas-Colell, A., Whinston, M.D. and J.R. Green (1995), Microeconomic Theory, Oxford University Press
Exam (written? If yes: One or two exam dates?): yes, four midterms and one final exam date (tba)

This course is devoted to the economic theory of preferences and choice, consumer choice, demand, production, market equilibrium, decision making under uncertainty, and game theory. The intention of the course is to familiarize students with the advanced tools of modern microeconomic theory.

This course is devoted to the economic theory of preferences and choice, consumer choice, demand, production, market equilibrium, decision making under uncertainty, and game theory. The intention of the course is to familiarize students with the advanced tools of modern microeconomic theory.

This course is devoted to the economic theory of preferences and choice, consumer choice, demand, production, market equilibrium, decision making under uncertainty, and game theory. The intention of the course is to familiarize students with the advanced tools of modern microeconomic theory.

This course is devoted to the core elements of microeconomics. We study both the economics of households and the economics of firms and introduce general equilibrium with particular attention to the two welfare theorems. We also examine decisions under uncertainty, introducing expected and non-expected utility theories. The analysis of choice under uncertainty leads to the examination of financial markets and to strategic interaction problems, which we introduce through the key notions in noncooperative game theory, in particular Nash equilibrium and its most important refinements. Also matching problems will be discussed.

This course is devoted to market failures and welfare economics. The first part addresses fundamental issues of welfare economics from the perspective of a policy maker who designs and implements collective decisions. It focuses in particular on social choice theory, the foundations of bargaining and welfare economics, and mechanism design. The second part focuses on the three classical conditions under which market outcomes lead to an inefficient allocation of resources: externalities, imperfect competition and asymmetric information. It addresses these questions both from a positive and normative perspective. The intention of the course is to familiarize students with the standard tools of modern economic theory and to train them in applying these tools to actual economic problems.

Literature:
Mas-Colell, Whinston, and Green (1995), Microeconomic Theory, Part III and Part V

This course is devoted to market failures and welfare economics. The first part focuses on the three classical conditions under which market outcomes lead to an inefficient allocation of resources: externalities, imperfect competition and asymmetric information. It addresses these questions both from a positive and normative perspective. The second part addresses fundamental issues of welfare economics from the perspective of a policy maker who designs and implements collective decisions. It focuses in particular on social choice theory, the foundations of bargaining and welfare economics, and mechanism design. The intention of the course is to familiarize students with the standard tools of modern economic theory and to train them in applying these tools to actual economic problems.

Literature: Mas-Colell, Whinston, and Green (1995), Microeconomic Theory, Part III and Part V

Description of the course:
This course is devoted to market failures and welfare economics. The first part focuses on the three classical conditions under which market outcomes lead to an inefficient allocation of resources: externalities, imperfect competition and asymmetric information. It addresses these questions both from a positive and normative perspective. The second part addresses fundamental issues of welfare economics from the perspective of a policy maker who designs and implements collective decisions. It focuses in particular on social choice theory, the foundations of bargaining and welfare economics, and mechanism design. The intention of the course is to familiarize students with the standard tools of modern economic theory and to train them in applying these tools to actual economic problems.

Literature:
Mas-Colell, Whinston, and Green (1995), Microeconomic Theory, Part III and Part V

Description of the course:
This course is devoted to market failures and welfare economics. The first part focuses on the three classical conditions under which market outcomes lead to an inefficient allocation of resources: externalities, imperfect competition and asymmetric information. It addresses these questions both from a positive and normative perspective. The second part addresses fundamental issues of welfare economics from the perspective of a policy maker who designs and implements collective decisions. It focuses in particular on social choice theory, the foundations of bargaining and welfare economics, and mechanism design. The intention of the course is to familiarize students with the standard tools of modern economic theory and to train them in applying these tools to actual economic problems.

Literature:
Mas-Colell, Whinston, and Green (1995), Microeconomic Theory, Part III and Part V

at Ferdinand Friedensburg Room 22008, DIW Berlin. On June 12 in R12026

Description:

This course discusses advantages and limitations of structural econometric models to give students an understanding of why and when adding structure is important. It also provides insights into strategy in important papers in structural Labor, Public and IO literature and establishes basic estimation techniques and numerical methods such as Simulation, Numerical integration and Discretisation. Besides of that, the course provides introduction to the matrix programming language MatLab.

The course aims at providing the basic concepts and methods for analysing time series data. The focus is on univariate modelling tools. The lecture begins with classical components models. Then we cover different types of stochastic processes like ARIMA and GARCH models, deal with the unit root methodology and procedures for forecasting as well as for the specification, estimation and validation of models. Multivariate extensions are demonstrated, with emphasis on vector autoregressive (VAR) processes and its application in causality and impulse response analyses. Nonstationary systems with integrated and cointegrated variables will also be treated.

In the tutorials the time series methods are applied to empirical data. We will intensively make use of econometric software packages. A deeper insight into advanced methods and additional topics is offered by means of assignments, empirical studies and/or literature reviews.

What is a causal effect and how can we identify and estimate a causal effect from nonexperimental data? These are among the most important questions in applied econometric research. This course will give an introduction and overview over the most important concepts and methods in this field, including the Rubin model of causality, the Roy model, statistical matching, instrumental variables, difference-in-differences methods, switching regression models, regression discontinuity design.